Create app.py

app.py

@@ -0,0 +1,18 @@
+model_path = '/content/drive/My Drive/Bart_samsum'
+
+from transformers import pipeline
+
+# Load the tokenizer and model from the specified path
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_path)
+
+# Create a pipeline for text summarization
+summarizer = pipeline("summarization", model=model, tokenizer=tokenizer)
+
+# Example input for inference
+
+# Perform inference
+summary = summarizer(dialogue, max_length=500, min_length=300, do_sample=False)
+
+# Print the summary
+print("Summary:", summary[0]['summary_text'])